From 5d8acfdc09be5ee1b3f73c3e711e18856172318a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=D0=A0=D0=B8=D0=BD=D0=B0=D1=80=20=D0=9C=D0=B8=D1=80=D0=B7?= =?UTF-8?q?=D0=B0=D0=B3=D0=B8=D1=82=D0=BE=D0=B2?= Date: Wed, 17 Jun 2026 13:10:09 +0000 Subject: [PATCH] =?UTF-8?q?=D0=9E=D0=B1=D0=BD=D0=BE=D0=B2=D0=BB=D0=B5?= =?UTF-8?q?=D0=BD=20vectorstore.py:=20remove=20documents/chroma=5Fintro.tx?= =?UTF-8?q?t?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- documents/chroma_intro.txt | 5 ----- 1 file changed, 5 deletions(-) delete mode 100644 documents/chroma_intro.txt diff --git a/documents/chroma_intro.txt b/documents/chroma_intro.txt deleted file mode 100644 index 810bd26..0000000 --- a/documents/chroma_intro.txt +++ /dev/null @@ -1,5 +0,0 @@ -ChromaDB is a local vector store that can persist embeddings between runs. - -With LangChain you can wrap Chroma as a vector store and then expose it as a retriever for semantic search. - -This is useful for local course notes and internal documents that should be searched without going to the web.